ID 原文 译文
58128 设计入簇函数与转发函数，降低恶意节点参与数据传输的几率. The cluster function and forwarding function are designed toreduce the chance of malicious nodes participating in data transmission.
58129 仿真结果表明，所提协议与LEACH-C 协议和 TLES 协议相比，数据包数目与能耗均衡性均得到较大提高，提升了无线传感器网络的安全性与可靠性. Simulation results show that，compared with LEACH-C and TLES protocols，both the number of data packets and the energy consumptionbalance have been greatly improved，enhancing the security and reliability of wireless sensor networks.
58130 为提高智能手机对人体运动状态识别的准确率，提出一种基于并联卷积神经网络( PCNN) 的深度识别方法. In order to improve the accuracy of recognition of human motion states by smart phones，an indepth recognition method based on parallel convolution neural network ( PCNN) is proposed.
58131 首先，使用三维数据矩阵规范传感器数据输入格式; Firstly，thesensor data input format is standardized by using 3D data matrix.
58132 其次，使用 2 个 PCNN 分别对人体运动的加速度传感器和陀螺仪数据进行卷积和池化操作，实现部分权重共享; Secondly，two PCNNs are used to carryout convolution and pool operation to the acceleration sensor and gyroscope data of human body motion respectively，realizing partial weight sharing.
58133 最后，在全连接层对两组卷积神经网络进行合并，并使用 softmax函数对人体运动状态进行分类. Finally，the two PCNNs are merged in the full-connected layer，and the softmax function is used to classify the human motion states.
58134 实验结果表明，采用该方法可以从传感器原始数据中提取人体运动状态的深层特征，与传统的机器学习方法相比较，提高了运动状态的识别率. Experiments show that thismethod can extract the deep features of human motion states from the original data of the sensor，whichcan improve the recognition rate of the motion state by comparing with the traditional machine learningmethod.
58135 针对多用户－多移动边缘计算服务器系统的动态计算任务卸载问题，基于用户端和服务器端的任务队列模型，以系统的长期平均时延和长期平均功耗为优化目标，求解最优的卸载策略及相应的上行预编码. Considering task queue model on both user and mobile edge computing ( MEC) server side，adynamic computing task offloading problem in multi-user-multi-MEC-server system is proposed. To findthe optimal offloading and corresponding uplink precoding strategy，a long-term average overhead containing delay and power consumption of the whole system optimization problem is formulated.
58136 通过李雅普诺夫优化方法将长期平均问题转化成单阶段目标优化问题，考虑到卸载策略和预编码之间存在范数约束关系，通过连续近似和半正定松弛，可转化成典型的 DC 规划求预编码解问题. The originalproblem is transformed into a single-stage cost target optimization problem based on Lyapunov optimizationmethod and further converted into a typical DC programming problem by utilizing successive approximation and semi-definite relaxation.
58137 仿真结果表明，所提方案比传统方法具有更低的时延和功耗. Simulation shows that the proposed scheme characterized by optimizingprecoding design can meet the lower delay and power consumption requirements.